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| title: Mbti Pocketflow | |
| emoji: 🔥 | |
| colorFrom: pink | |
| colorTo: gray | |
| sdk: gradio | |
| sdk_version: 5.38.2 | |
| app_file: app.py | |
| pinned: false | |
| short_description: PocketFlow application for conducting Myers-Briggs + llm | |
| # MBTI Personality Questionnaire | |
| A PocketFlow-based application for conducting Myers-Briggs Type Indicator (MBTI) personality assessments with both traditional scoring and AI analysis. | |
| ## Features | |
| - **20/40/60-question MBTI questionnaire** with selectable length for accuracy | |
| - **Traditional scoring algorithm** for baseline personality type determination | |
| - **AI-powered analysis** using LLM for detailed personality insights with question references | |
| - **Interactive Gradio web interface** with auto-save and progress tracking | |
| - **HTML report generation** with clickable question references and comprehensive analysis | |
| - **Data export/import** for saving and resuming questionnaires | |
| - **CLI and test modes** for different use cases | |
| ## Project Structure | |
| ``` | |
| /mbt/ | |
| ├── utils/ | |
| │ ├── call_llm.py # LLM integration (Gemini) | |
| │ ├── questionnaire.py # Question sets (20/40/60) and loading/saving | |
| │ ├── mbti_scoring.py # Traditional MBTI scoring | |
| │ ├── report_generator.py # HTML report generation with markdown support | |
| │ └── test_data.py # Test data generation | |
| ├── nodes.py # PocketFlow nodes (LoadQuestionnaire, LLMAnalysis, etc.) | |
| ├── flow.py # PocketFlow flow definition | |
| ├── app.py # **Main Gradio web interface with LLM** | |
| ├── pf_cli.py # PocketFlow CLI interface | |
| └── requirements.txt # Dependencies | |
| ``` | |
| ## Quick Start | |
| ### 1. Web Interface (Recommended) | |
| ```bash | |
| # Install dependencies | |
| pip install -r requirements.txt | |
| # Set up Gemini API key | |
| export GEMINI_API_KEY="your-api-key-here" | |
| # Or on Windows: | |
| set GEMINI_API_KEY=your-api-key-here | |
| # Run Gradio web interface | |
| python app.py | |
| ``` | |
| Then open http://127.0.0.1:7860 in your browser. | |
| ### 2. Command Line Interface | |
| ```bash | |
| # Run CLI questionnaire | |
| python pf_cli.py | |
| # Run with test data | |
| python pf_cli.py --test --test-type INTJ | |
| # Import previous questionnaire | |
| python pf_cli.py --import-file questionnaire.json | |
| ``` | |
| ## Usage Examples | |
| ### Gradio Web Interface | |
| ```bash | |
| python app.py | |
| ``` | |
| - **Interactive web interface** at http://127.0.0.1:7860 | |
| - **Question length selection** (20/40/60 questions) | |
| - **Auto-save responses** as you navigate | |
| - **Progress tracking** and export functionality | |
| - **AI analysis** with clickable question references | |
| - **HTML report generation** with comprehensive insights | |
| - **Load/save questionnaires** for resuming later | |
| ### Command Line Interface | |
| ```bash | |
| python pf_cli.py | |
| ``` | |
| - **Complete PocketFlow architecture** | |
| - **Traditional scoring** with optional LLM analysis | |
| - **Automatic report generation** | |
| - **Data import/export** in JSON format | |
| ### Test Modes | |
| ```bash | |
| # CLI test with specific MBTI type | |
| python pf_cli.py --test --test-type ENFP | |
| ``` | |
| ### Import/Export | |
| ```bash | |
| # Export: Questionnaire data automatically saved as: | |
| # mbti_questionnaire_pf_partial_[COUNT]q_[TIMESTAMP].json | |
| # Import: Load previous questionnaire | |
| python pf_cli.py --import-file questionnaire.json | |
| ``` | |
| ## MBTI Types Supported | |
| The application recognizes all 16 MBTI personality types: | |
| **Analysts:** INTJ, INTP, ENTJ, ENTP | |
| **Diplomats:** INFJ, INFP, ENFJ, ENFP | |
| **Sentinels:** ISTJ, ISFJ, ESTJ, ESFJ | |
| **Explorers:** ISTP, ISFP, ESTP, ESFP | |
| ## Key Features | |
| ### Question Sets | |
| - **20 questions:** Quick assessment (5 per dimension) | |
| - **40 questions:** Balanced assessment (10 per dimension) | |
| - **60 questions:** Comprehensive assessment (15 per dimension) | |
| ### AI Analysis | |
| - **Question-specific insights** with clickable references like [Q1](#Q1) | |
| - **Out-of-character response detection** and explanations | |
| - **Evidence-based analysis** citing specific question responses | |
| - **Behavioral pattern identification** | |
| - **Strengths and growth areas** based on actual responses | |
| ### Web Interface Features | |
| - **Auto-save** responses on navigation | |
| - **Progress tracking** with completion indicators | |
| - **Export progress** at any time (partial questionnaires) | |
| - **Load previous sessions** to continue where you left off | |
| - **Immediate download** of reports and data | |
| ## Development | |
| ### Adding New Features | |
| 2. Implement utility functions in `utils/` | |
| 3. Create or modify nodes in `nodes.py` | |
| 4. Update flow in `flow.py` | |
| 5. Test with CLI and web interface | |
| ## Dependencies | |
| **Required:** | |
| - Python 3.8+ | |
| - gradio>=4.0.0 (web interface) | |
| - google-genai>=0.3.0 (LLM analysis) | |
| - beautifulsoup4 (HTML parsing) | |
| - markdown (report generation) | |
| **Optional:** | |
| - pydantic (enhanced data validation) | |
| See `requirements.txt` for complete list. | |
| ## File Overview | |
| - **`gradio_pf_llm.py`** - Main web interface with full LLM analysis | |
| - **`pf_cli.py`** - Command line interface using PocketFlow architecture | |
| - **`nodes.py`** - PocketFlow node implementations | |
| - **`flow.py`** - PocketFlow pipeline definition | |
| - **`utils/`** - Core utility functions (questionnaire, scoring, reports, LLM) | |
| ## License | |
| This project follows PocketFlow's open-source approach for educational and research purposes. | |